How do you measure code quality? what are code coverage tools?

3 Mins read

If you asked yourself How do you measure code quality? You are definitely on the article that will You can measure code quality with a bunch of different tools. Some use static analysis to detect errors and potential security vulnerabilities. Others use dynamic analysis to monitor the resource usage of your application as well as its performance against expected values.

Most tools will provide some level of metrics as well as suggestions for how to improve your application’s quality, but their accuracy and usefulness depend on the tool itself. You may find that depending on what team or company you work for, there are specific metrics that matter more than others – like a specific number of security vulnerabilities, or a specific amount of CPU usage, or a specific amount of memory consumed.

There is no right number or exact reference point for how much code is of quality – It’s directly tied to the globally significant metrics that matter most to your company’s goals.

Some laboratories and organizations use multiple methods of measurement provided by the different tools. They may use static analysis, dynamic analysis and other techniques to get a comprehensive view of code quality.

Choose a tool to measure code quality – these are some of the most popular: Apache JMeter – Java Testing Framework – see about performance and load testing here.
Checkstyle – Java, C++, SQL
CodeSonar – Code quality analysis tool
Clover Code Analysis – Static Analysis for C Code

What is code coverage and how do you measure code quality?

Code coverage is a measurement of how much of your code is actually executed. It determines how many lines are executed in your code versus what was actually written.
Some tools use static analysis to determine if the code is executed.

Others will monitor the behaviour of the code by instrumenting it so that their analysis will know what it is doing at any given time. If you have a slow call to a database or network component, they can monitor this and measure how much time was spent waiting for the remote server to respond.

The usefulness of displaying this information depends on how often you change your system or application.

Other types of metrics include cyclomatic complexity, coupling, cohesion, information flow control and others.

What is cyclomatic complexity?

Cyclomatic complexity is a method of calculating how complex your code is. It determines how many different paths are possible through your code. This can be useful to determine if you have any unnecessary or redundant control structures embedded in the code.

Some tools use static analysis to determine this value, others use dynamic analysis to calculate the number of times certain paths are taken through your application after it has been deployed into production.

What is coupling?

Coupling refers to the number of other components that are dependent on a particular module or function being executed.

How do you know that the code coverage is enough?

The concept behind code coverage is that it provides an indication of how much of the input source code was executed during testing.

This metric may be used in various testing scenarios: unit tests, integration tests and regression tests. As we know, the unit test should only test a single module or function at a time and can help us eliminate bugs in small parts of our application.

Many tools and methodologies measure this concept (linting, sum types) but others choose not to make this measurement part of their strategy.

Examples of code coverage tools












We have seen how to measure code quality and what are the methods of analysis.
The most popular metrics are code coverage, cyclomatic complexity, coupling, cohesion, information flow control and others.

Nowadays with the help of different tools, you can monitor these metrics for free or for a small fee.While applications are now available as open-source software that you download from the internet to see how they are built, including their code quality metrics.
Programmers may now be held accountable for bad practices through the automated process.

Software development is an area that requires a detailed analysis of source code quality in order to ensure the safety and protection of data sources against any type of attack.

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